Capturing Patients' Perspectives on Medication Safety: The Development of a Patient-Centered Medication Safety Framework
Bibliographic record
Abstract
OBJECTIVES: Medication safety incidents are common in primary care and contributory factors frameworks can assist in our understanding of their causes. A framework that is positioned from the perspective of patients would be advantageous in practice when seeking patient insights into medication safety. The aim of this study was to develop a patient-centered contributory factors framework for examining medication safety incidents. METHODS: A purposive sample of 106 members of the public, patients, and carers were recruited to take part in focus groups (n = 18). Focus groups were audio recorded, transcribed, and analyzed using a thematic framework. A patient and public involvement group was set up to undertake multiple roles in the research process, including the development of the focus group schedule, analysis of the data, and the construction of a patient-centered framework of contributory factors (patient-centered medication safety) and implementation checklist. RESULTS: The findings highlighted the importance of communication, supplies of medication and appliances, patient- and carer-related factors, healthcare professional factors, and computer systems and programs in the safe use of medicines. Some contributory factors were unique to primary care patients such as access to services and continuity of care. In conjunction with a patient and public involvement group, a framework of factors that patients believe contribute to medication safety incidents in primary care was developed that could be used by patients and healthcare professionals. CONCLUSIONS: The patient-centered medication safety framework and implementation checklist provides a novel tool to examine contributory factors that can lead to medication safety incidents from patients' perspective.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.097 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.004 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".